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Graph databases portray the data as it is viewed conceptually. This is accomplished by transferring the data into nodes and its relationships into edges. A graph database is a database that is based on graph theory. It consists of a set of objects, which can be a node or an edge.
InfiniteGraph is a distributed graph database implemented in Java and C++ and is from a class of NOSQL ("Not Only SQL") database technologies that focus on graph data structures. Developers use InfiniteGraph to find useful and often hidden relationships in highly connected, complex big data sets.
NoSQL databases use a variety of data models, with document, graph, and key–value models being popular. [2] A multi-model database is a database that can store, index and query data in more than one model. For some time, databases have primarily supported only one model, such as: relational database, document-oriented database, graph database ...
OrientDB is an open source NoSQL database management system written in Java. It is a Multi-model database, supporting graph, document and object models, [2] the relationships are managed as in graph databases with direct connections between records. It supports schema-less, schema-full and schema-mixed modes.
ArangoDB is a transactional native multi-model database supporting two major NoSQL data models (graph and document [1]) with one query language. Written in C++ and optimized for in-memory computing. In addition ArangoDB integrated RocksDB for persistent storage. ArangoDB supports Java, JavaScript, Python, PHP, NodeJS, C++ and Elixir.
NoSQL (originally referring to "non-SQL" or "non-relational") [1] is an approach to database design that focuses on providing a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. Instead of the typical tabular structure of a relational database, NoSQL databases ...
ArangoDB is a graph database system developed by ArangoDB Inc. ArangoDB is a multi-model database system since it supports three data models (graphs, JSON documents, key/value) [1] with one database core and a unified query language AQL (ArangoDB Query Language).
Firstly, the graph model can be a natural fit for data sets that have hierarchical, complex, or even arbitrary structures. Such structures can be easily encoded into the graph model as edges. This can be more convenient than the relational model, which requires the normalization of the data set into a set of tables with fixed row types.